"One of the major contributions of electroencephalography has been its application in the diagnosis and clinical evaluation of epilepsy." (Ktonas, 1987) However, descriptions of the rules used during the visual inspection of the EEG data are often subjective and can vary greatly from one EEG reader to the next. Computer automation is a means for objectifying this process; however, previous algorithms have failed to implement many of the visual interpretation methods used by humans, limiting their usefulness and abilities. The proposed research utilizes the PERSYST Waveform Interpreter, an expert system shell designed specifically for modeling the visual perception and cognition processes of human experts who interpret waveforms. This technology will be used to enhance the SSW Detector developed In Phase l so that the system can analyze seizures, as well as spikes and sharp waves at real time speeds. A "gold standard" spike database, created by a panel of expert EEG readers through consensus marking, will be used to validate the algorithm. In the future, it is believed that this technology can enhance the current trend towards quantified EEG, which shows promise for addressing a wide variety of issues in clinical neuroscience, including learning problems, aging, and schizophrenia.